import numpy as np
import csv
from datetime import datetime
from time import strftime


def getCurTime():
    """
    get current time
    Return value of the date string format(%Y-%m-%d %H:%M:%S)
    """
    format='%Y-%m-%d %H:%M:%S'
    sdate = None
    cdate = datetime.now()
    try:
        sdate = cdate.strftime(format)
    except:
        raise ValueError
    return sdate

def build_data_list(inputCSV):
    sKey = []
    fn = inputCSV
    f = open(inputCSV)
    #ra = csv.DictReader(file(fn), dialect="excel")
    ra = csv.DictReader(f, dialect="excel")
    
    for record in ra:
        #print record[ra.fieldnames[0]], type(record[ra.fieldnames[-1]])
        for item in ra.fieldnames:
            temp = int(float(record[item]))
            sKey.append(temp)
    sKey = np.array(sKey)
    sKey.shape=(-1,len(ra.fieldnames))
    return sKey

def cal_dist(x1, y1, x2, y2):
    temp_dist = (float(x1 - x2))**2 + (float((y1 - y2))**2)
    #print x1, y1, x2, y2, (float(x1 - x2))**2, (float((y1 - y2))**2), temp_dist
    temp_dist = temp_dist**0.5
    #print temp_dist

    return temp_dist

#--------------------------------------------------------------------------
#MAIN

if __name__ == "__main__":
    print '===================================================='
    print "begin at " + getCurTime()

    dataCSV = 'C:/_DATA/migration_census_2009/dataformat.csv'
    data = build_data_list(dataCSV) # [oid, didi, flow, error]

    filepath = 'C:/_DATA/migration_census_2009/REDCAPLUS_100Region/'
    idtableCSV = filepath + 'cnty_100regs_fid_regid.csv'
    idtable = build_data_list(idtableCSV)   #[fid, fips, stateid]

    Centroid_CSV = 'C:/_DATA/migration_census_2000/REDCAPLUS_100Region/redcaplus_100_centroid.csv'
    centroid = build_data_list(Centroid_CSV)

    n = len(centroid)
    distance = np.zeros((n,n))
    
    for i in range(len(centroid)-1):
        for j in range(i+1, len(centroid)):
            distance[i,j] = int(cal_dist(centroid[i, 0], centroid[i, 1], centroid[j, 0], centroid[j, 1]))
            distance[j,i] = distance[i,j]

    flowtable = np.zeros((n,n))
    
    for item in data:
        oid = idtable[item[0],-1]
        iid = idtable[item[1],-1]
        flowtable[oid, iid] += item[2]

    output = []
    inoutflow = np.zeros((n,2))

    for i in range(len(flowtable)):
        for j in range(len(flowtable[:,0])):
            if (flowtable[i,j] > 0) and (i <> j):
                inoutflow[j,0] += int(flowtable[i,j])
                inoutflow[i,1] += int(flowtable[i,j])
                output.append([int(distance[i,j]), i, j, int(flowtable[i,j])])

    fileLoc = filepath + 'migration_100regs_inoutflow.csv'
    headerstr = 'inflow,outflow'
    np.savetxt(fileLoc, inoutflow, delimiter=',', header = headerstr, fmt = '%i')

    headerstr = 'dist,OrigId,destId,flowVol'
    fileLoc = filepath + 'migration_100regs_dist.csv'
    np.savetxt(fileLoc, output, delimiter=',', header = headerstr, fmt = '%s')